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Research Fellow in Optical Fibre Transmission Systems/Networks

UCL - Optical Networks Group, Department of Electronic and Electrical Engineering

Location: London
Salary: £40,524 to £58,895
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 21st September 2023
Closes: 19th October 2023
Job Ref: B04-04249

About us

As a part of research under the EPSRC funded projects ‘Transforming networks - building an intelligent optical infrastructure (TRANSNET)’ and ‘Extremely Wideband Optical Communication Systems (EWOC)’ being carried out by the Optical Networks Group, Department of Electronic and Electrical Engineering at UCL, we are looking to recruit two researchers either at Research Fellow or Senior Research Fellow level.

The aims of the project are to investigate wideband, spectrally efficient data transmission, employing advanced signal formats and digital signal processing methods, with the aim of exploring the fundamental physical phenomena governing such systems and experimentally demonstrating world-record data throughputs for single-mode fibre systems.

About the role

One post is intelligent networks based. The researcher will:

  • Develop new AI/ML techniques for the analysis of core and data-centre network topologies
  • Develop new AI/ML based routing algorithms to maximise network throughput and minimise delays
  • Analyse the impact of network traffic statistics on network architectures and throughput
  • Develop universal network tools covering core, metro and access architectures as well as data centres and within high-performance computer architectures

The other post is experimental based. The researcher will:

  • Participate in the design and development of intelligent, ML-based transceivers and extremely wideband optical fibre transmission
  • Develop and apply ML-based methods for optical signal generation and detection, equalisation and fibre nonlinearity mitigation (e.g., neural networks, learned digital back-propagation, deep-learned auto-encoders) and other digital signal processing techniques
  • Design spectrally-efficient transmission systems exploiting the 1270nm – 1670nm wavelength band.
  • Develop and use computer simulations of the systems, including the effects of fibre nonlinearity (e.g., SPM, XPM and stimulated Raman scattering).
  • Carry out high-speed optical transmission experiments using straight line and recirculating loop testbeds in various transmission scenarios and explore the use of different sources, fibres, amplifiers, and nonlinear optical devices.

The posts are available from 1st January 2024 for 18 months in the first instance. Further funding to support the posts may be available.

About you

For both posts, applicants should have a PhD (or about to submit) in a relevant branch of science or engineering (Electronic Engineering, Information Engineering or Physics). Knowledge of noise, distortion/nonlinearity and crosstalk from electronic and optoelectronic devices is essential, as well as knowledge of advanced electronic and optical test instruments (e.g., spectrum analyser, oscilloscopes, arbitrary waveform generators).

For the intelligent networks based post, applicants should demonstrate knowledge of machine learning methods for optical networks including reinforcement learning, graph neural networks and operations research approaches. Experience developing programs implementing machine learning algorithms (e.g., use of TensorFlow, PyTorch, JAX) is required.

For the experimental based post, candidates should possess hands-on experience of state-of-the art test & measurement equipment (spectrum analyser, oscilloscopes, arbitrary waveform generators) and their control for automation of research experiments.

To be appointed at Senior Research Fellow level, the successful candidate will have significant post-doctoral experience on research (theoretical and experimental) associated with optical fibre communications.

Application details:

  • Applications close on 19th October, 23:59.
  • A job description and person specification can be accessed at the apply link, as well as contact details for queries about the post.
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